The use of animation in diagrams has recently gained prominence for visualizing trends in multi-dimensional data during presentations. In general, the word “trend” means to have a general tendency, such that a trend in data is an observed general tendency of the data. One common way to visualize trends in data is to plot a variable's change over time on a line chart (or bar chart). If there is a general increase or decrease over time, this is perceived as a trend up or down. On the other hand, if there is a general increase or decrease that reverses direction, it is perceived as a reversing trend. If there are more than a few reversals, it appears to be cyclic or noisy data, and no trend is perceived.
Several types of animation techniques are currently available for visualizing data trends using diagrams. In one technique, the use of animation together with interesting data and a highly engaging presenter provide a dramatic impact. This animation technique uses animation to illustrate trends in multi-dimensional data. This technique uses an animated (or dynamic) bubble chart to show three dimensions of data, one for the X-axis, one for the Y-axis, and one for the bubble size, animated over changes in a fourth dimension (time). For example, when looking at United Nations statistics for various countries, the X-axis might show life expectancy, the Y-axis might show infant mortality rate, and the bubble size might show population size, with each bubble representing a country. The trend over time is shown as an animation over time, with the bubbles changing position and size to indicate the current data values for each country at a particular time. For example, the animation may show a general trend for most countries to increase life expectancy while decreasing infant mortality rate.
This technique is quite effective in a presentation setting. The presenter already knows the direction of the data trend flow and directs the observer's attention to an area of interest in the diagram. Once the observer knows where to look, the animation makes the data come to life and emphasizes the critical results of an analysis. This has been done with large screens and has evoked a strong favorable response from audiences.
During analysis or data exploration, however, there is no presenter telling the user of the diagram where to look. In practice, this means the user, in most cases, must replay the animation several times to process trend developments in the animated diagram and identify the direction of data trend flow and any anomalies in the trends. Consequently, this animation technique is much less effective for analysis and data exploration situations. Without a presenter directing the user's attention, the user will notice changes but not know exactly where to look in the diagram without repeatedly viewing the diagram.
At least one other animation technique adds the ability to collapse related bubbles into an aggregate bubble (such as, in the example above, to show one bubble for a continent). This aggregation animation technique reduces clutter and occlusion, but anomalies of interest are potentially hidden from view. Another technique uses a moving bubble chart, which adds the ability to identify which dimensions of a data cube to map to which axes. These animated techniques, however, still work best in a data presentation setting as compared to a data analysis setting.